Paraformer-zh · GGUF (FunASR llama.cpp runtime)
2
10 commits
2 linked in READMEs
updated Jul 26, 2026
GGUF build of FunASR's Paraformer-zh (SAN-M encoder + CIF predictor + SAN-M decoder, non-autoregressive) for the zero-Python, CPU/edge FunASR llama.cpp runtime — fast Mandarin ASR, ~21× real-time on CPU.
These are GGUF weights for the FunASR llama.cpp runtime — a whisper.cpp-style, single self-contained binary for CPU / edge. Grab a prebuilt binary, then fetch this model and run:
runtime-llamacpp-v*)bash download-funasr-model.sh paraformer ./gguf
llama-funasr-paraformer -m ./gguf/paraformer-q8.gguf --vad ./gguf/fsmn-vad.gguf -a audio.wav
| file | size | notes |
|---|---|---|
paraformer-f16.gguf | 435 MB | recommended (f16 matmul weights) |
paraformer-q8.gguf | ~217 MB | recommended — half of f16, same accuracy |
paraformer.gguf | 863 MB | f32 reference |
The binary prints transcription text directly (no Python detok). --ids for raw ids.
llama-funasr-paraformer -m paraformer-f16.gguf -a audio.wav --vad fsmn-vad.gguf
On CPU (8 threads): 9.85 % CER on the 184-clip Mandarin benchmark (vs whisper.cpp 22–31 %).
Paraformer-zh · GGUF (FunASR llama.cpp runtime)
2
10 commits
2 linked in READMEs
updated Jul 26, 2026
GGUF build of FunASR's Paraformer-zh (SAN-M encoder + CIF predictor + SAN-M decoder, non-autoregressive) for the zero-Python, CPU/edge FunASR llama.cpp runtime — fast Mandarin ASR, ~21× real-time on CPU.
These are GGUF weights for the FunASR llama.cpp runtime — a whisper.cpp-style, single self-contained binary for CPU / edge. Grab a prebuilt binary, then fetch this model and run:
runtime-llamacpp-v*)bash download-funasr-model.sh paraformer ./gguf
llama-funasr-paraformer -m ./gguf/paraformer-q8.gguf --vad ./gguf/fsmn-vad.gguf -a audio.wav
| file | size | notes |
|---|---|---|
paraformer-f16.gguf | 435 MB | recommended (f16 matmul weights) |
paraformer-q8.gguf | ~217 MB | recommended — half of f16, same accuracy |
paraformer.gguf | 863 MB | f32 reference |
The binary prints transcription text directly (no Python detok). --ids for raw ids.
llama-funasr-paraformer -m paraformer-f16.gguf -a audio.wav --vad fsmn-vad.gguf
On CPU (8 threads): 9.85 % CER on the 184-clip Mandarin benchmark (vs whisper.cpp 22–31 %).